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SHAP

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SHapley Additive exPlanations: a feature-attribution method that assigns each input feature a share of a particular prediction, based on Shapley values 1; its explanations depend on the chosen baseline or background data.

Developed in
ch. 16, Feature attribution: SHAP, LIME and integrated gradients
Chapters
ch. 16, Fairness & XAI
Contrast with
LIME
Source
1 numbered reference, listed below

Where it is used

One chapter of the Body of Knowledge uses the term. Each link opens the first section that does.

Patterns that use this term

One pattern page uses the term.

Sources

  1. [1] "A Unified Approach to Interpreting Model Predictions" (Lundberg and Lee; SHAP; arXiv 1705.07874). arXiv. 2017-05-22. https://arxiv.org/abs/1705.07874 (verified: primary)

Definitions of legal terms paraphrase the cited text, which governs. Dated statements are as of .

Cite this term

García Aibar, J. (2026). SHAP. In AI Governance Engineering: The Thesis & Body of Knowledge (v0.5.0), Glossary. https://doi.org/10.5281/zenodo.22956197. https://aigovernanceengineer.com/glossary/shap. CC BY 4.0

BibTeX

@misc{aige2026shap,
  author  = {Jorge García Aibar},
  title   = {{SHAP}},
  note    = {Glossary, AI Governance Engineering: The Thesis \& Body of Knowledge, version 0.5.0},
  year    = {2026},
  doi     = {10.5281/zenodo.22956197},
  url     = {https://aigovernanceengineer.com/glossary/shap}
}